Rocket Data Replicate and Sync (formerly tcVISION): Enterprise ETL and Real-Time Data Replication Through Change Data Capture

Rocket Data Replicate and Sync (RDRS) provides an easy and fast approach for hybrid cloud projects. RDRS enables bi-directional data replication between the hardware and Cloud, LUW, and Open Systems platforms.

The globalization of markets, the increase of data volumes, 24x7 operations, changing business conditions and high demand for up-to-date information require new data transfer and exchange solutions for heterogeneous IT architectures.

The RDRS solution focuses on changed data capture (CDC) when transferring information between mainframe data sources and Cloud, LUW, Open System databases and applications. Through an innovative technology, changes occurring in any mainframe application data are tracked and captured, and then published to a variety of RDBMS and other targets.

RDRS' capture facilities detect changes in mainframe data sources without programming effort, and reduce the amount of data that must be transferred between systems to an absolute minimum. RDRS guarantees transparent, efficient and auditable data transfer between sources and targets, and provides powerful routines to perform efficient, reliable bulk transfers of data. The RDRS solution focuses on changed data when transferring information between mainframe and LUW data sources.

RDRS is an innovative technology that offers comprehensive abilities to identify and capture changes occurring in mainframe and relational databases, then publish the required information to a variety of targets.

RDRS (tcVISION) in 90 Seconds...

The RDRS Solution
  • Modeling and mapping via a GUI modeler.

  • Bi-directional replication for a variety of non-mainframe sources, including Amazon Web Services (AWS), Microsoft Azure, Google Cloud, Oracle Cloud, Oracle Database, Microsoft SQL Server, IBM Db2 LUW and Db2 BLU, IBM Informix, PostgreSQL, etc.

  • Big Data is a standard output platform.

  • Allows mainframe data to quickly and easily be integrated in near real-time into Hadoop-based operative applications or Business Intelligence and Analytics.

  • Change capture facilities identify changes in mainframe and relational data sources without programming effort.

  • Transfers the changed data to target mainframe and relational databases and applications in real time, in time intervals or in response to events.

  • Guarantees transparent and auditable data transfer between sources and targets.

  • Provides powerful processors to perform fast, efficient and reliable transfers of mass data.

  • Delivers drastic savings for all mainframe-related data exchange operations. Change Data Capture reduces costs: less processing time, less hardware and less human resources are needed for exchange of information.

  • Reduces the amount of data that must be transferred between the different systems to an absolute minimum.

  • Only data that has been changed is transferred--only data that is really needed will be moved.

Supported Environments

IBM-Mainframe: IBM z/OS, VSE

Target database can reside on a workstation, Cloud (AWS, Microsoft Azure, Google Cloiud, etc.), or on an open systems or Windows server (e.g., Oracle, SQL Server, Sybase, etc.)--or another mainframe database (e.g., DL/1 -> DB2).

Transfer to the target system: SQL, HTML, XML or any user-specific format that can be accessed by an API


Read More: Supported Sources and Targets

Read More: AWS Blog -"Real-Time Mainframe Data Replication to AWS with RDRS (tcVISION)"

Read More: Main page

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